Machine learning on graphs | Vidéo | Carmin.tv

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Machine learning on graphs

De Pierre Vandergheynst

Apparaît dans la collection : Theoretical Computer Science Spring School: Machine Learning / Ecole de Printemps d'Informatique Théorique : Apprentissage Automatique

There are a plethora of interesting applications that can leverage graph structured data, from drug discovery to route planning, and it is only natural that graph Machine Learning has attracted a lot of attention lately. We will review approaches in graph representation learning, leveraging intuition from graph signal processing to design and study graph neural networks and some of their recent extensions.

Informations sur la vidéo

Date de captation 23/05/2022
Date de publication 21/06/2022
Institut CIRM
Licence CC BY NC ND
Langue Anglais
Audience Chercheurs, Doctorants
Réalisateur(s) Jean Petit
Format MP4

Données de citation

DOI 10.24350/CIRM.V.19921603
Citer cette vidéo Vandergheynst, Pierre (23/05/2022). Machine learning on graphs. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19921603
URL https://dx.doi.org/10.24350/CIRM.V.19921603

Domaine(s)

Informatique et langage

Bibliographie

HAMILTON, William L., YING, Rex, et LESKOVEC, Jure. Representation learning on graphs: Methods and applications. arXiv preprint arXiv:1709.05584, 2017. - https://doi.org/10.48550/arXiv.1709.05584
CHUNG, Fan RK et GRAHAM, Fan Chung. Spectral graph theory. American Mathematical Soc., 1997. - https://bookstore.ams.org/cbms-92
BRONSTEIN, Michael M., BRUNA, Joan, LECUN, Yann, et al. Geometric deep learning: going beyond euclidean data. IEEE Signal Processing Magazine, 2017, vol. 34, no 4, p. 18-42. - https://doi.org/10.1109/MSP.2017.2693418

Codes MSC

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